Template-Type: ReDIF-Article 1.0 Author-Name: Siyue Wang Author-X-Name-First: Siyue Author-X-Name-Last: Wang Author-Name: Weisheng Wang Author-X-Name-First: Weisheng Author-X-Name-Last: Wang Title: Social network analysis method of teaching constraints and development approach of online courses Abstract: In order to overcome the low student participation rate, homework completion rate and course satisfaction existing in the traditional analysis method of online course teaching constraints and development paths, a social network analysis method of teaching constraints and development approach of online courses is proposed. Calculate the network density of social network and the centrality between points, identify the key time points or events that affect the teaching effect of online courses, thus determine the constraints of online course teaching, including technology, resources, educational environment and student factors, and analyse the development path of online course teaching from the aspects of technological innovation and application, updating teaching concepts, optimising course design and management, and strengthening resource integration and sharing. The experimental results show that the average student participation rate is 97.17%, the average homework completion rate is 96.79%, and the course satisfaction is always above 96.6. Journal: Int. J. of Networking and Virtual Organisations Pages: 49-69 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: social network analysis; online courses; constraints; development approach; network density; centrality between points. File-URL: http://www.inderscience.com/link.php?id=145363 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:49-69 Template-Type: ReDIF-Article 1.0 Author-Name: Yali Zhang Author-X-Name-First: Yali Author-X-Name-Last: Zhang Title: Study on comprehensive management of online learning resources for digital education and teaching reform Abstract: In order to improve the efficiency of utilising online learning resources and the quality of students' learning, this paper proposes a comprehensive management method for online learning resources aimed at digital education and teaching reform. Firstly, this paper provides a detailed explanation of the definition, classification, and application of online learning resources in education. Furthermore, this paper conducts an in-depth analysis of the resource merging and classification problems and recommendation issues in current online learning resource management, and points out the challenges of these problems. On this basis, this paper adopts an adaptive sliding window mutual information method to extract the features of network learning resources, thereby achieving resource merging and classification management. The experimental results show that under the background of digital education and teaching reform, the method proposed in this paper can not only effectively classify and manage online learning resources. Journal: Int. J. of Networking and Virtual Organisations Pages: 36-48 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: digital education; teaching reform; online learning resources; comprehensive management; LDA user interest model; sliding window mutual information method. File-URL: http://www.inderscience.com/link.php?id=145364 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:36-48 Template-Type: ReDIF-Article 1.0 Author-Name: Xiaobo Zhang Author-X-Name-First: Xiaobo Author-X-Name-Last: Zhang Author-Name: Ketong Liu Author-X-Name-First: Ketong Author-X-Name-Last: Liu Author-Name: Yan Zhang Author-X-Name-First: Yan Author-X-Name-Last: Zhang Title: Resource allocation of distributed wireless network based on mobile edge computing Abstract: In order to solve the problems of high packet loss rate, low configuration balance and long time in traditional resource allocation methods, a resource allocation method of distributed wireless network based on mobile edge computing is proposed. The mobile edge computing is used to select the distributed wireless network service nodes, so as to determine the constraints such as task unloading, resource allocation, task execution delay, transmission rate, etc., build the distributed wireless network resource allocation objective function, and use the genetic-annealing algorithm to solve the objective function. The optimal solution is the optimal distributed wireless network resource allocation scheme. The experimental results show that the average packet loss rate of this method is 3.06%, the resource allocation balance of distributed wireless network varies from 0.96 to 0.96, and the average allocation time is reduced by 2.12 s and 1.19 s respectively compared with the two experimental comparison methods. Journal: Int. J. of Networking and Virtual Organisations Pages: 1-20 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: mobile edge computing; distributed; wireless network; resource allocation; constraints; objective function; genetic-annealing algorithm. File-URL: http://www.inderscience.com/link.php?id=145365 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:1-20 Template-Type: ReDIF-Article 1.0 Author-Name: BinBin Yan Author-X-Name-First: BinBin Author-X-Name-Last: Yan Title: Evaluation of interactive teaching effectiveness under social network analysis Abstract: In order to effectively improve the accuracy and comprehensiveness of evaluation results, a method for evaluating the effectiveness of online interactive teaching under social network analysis is proposed. Firstly, collect online interactive teaching data and use Pearson correlation coefficient to calculate the correlation coefficient between the data, filtering out indicators significantly related to teaching effectiveness. Secondly, use information entropy to calculate the weight of evaluation indicators. Finally, construct a social network model, measure the node intimacy function, and identify important nodes in the social network to optimise the social network model and more accurately evaluate teaching effectiveness. The experimental results show that the highest accuracy value of the method proposed in this paper is 95%, the highest precision value is 72%, and the highest recall value is 92%, all of which are better than existing methods, fully demonstrating the effectiveness of its teaching effectiveness evaluation. Journal: Int. J. of Networking and Virtual Organisations Pages: 21-35 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: social network; interactive teaching; effect evaluation; Pearson correlation coefficient; indicators significantly; node intimacy function. File-URL: http://www.inderscience.com/link.php?id=145366 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:21-35 Template-Type: ReDIF-Article 1.0 Author-Name: Zihan Gao Author-X-Name-First: Zihan Author-X-Name-Last: Gao Title: Online financial product marketing information push method based on social relationship network analysis Abstract: The research on online financial product marketing information push is of great significance for improving the efficiency of financial institutions, optimising product design, and promoting financial technology innovation and digital transformation. In order to solve the problems existing in current methods, an online financial product marketing information push method based on social relationship network analysis is proposed. This method uses social network to analyse and calculate the influence of user relationship, and combines with two-way gated recurrent unit (GRU) neural network to extract user interest. Push online financial product marketing information based on user interests and multi-Markov chain. Experimental results show that the proposed method performs well in accuracy, push time and user retention rate. Therefore, this method has the characteristics of high precision and high efficiency. Journal: Int. J. of Networking and Virtual Organisations Pages: 70-85 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: social relationship network analysis; online financial product; marketing information push; two-way GRU neural network; multi-Markov chain. File-URL: http://www.inderscience.com/link.php?id=145370 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:70-85 Template-Type: ReDIF-Article 1.0 Author-Name: Yi Liu Author-X-Name-First: Yi Author-X-Name-Last: Liu Author-Name: Fu Peng Author-X-Name-First: Fu Author-X-Name-Last: Peng Title: Personalised learning resource online recommendation method based on multi-dimensional feature extraction Abstract: In order to optimise the effectiveness of resource recommendation and improve the coverage of personalised learning resource recommendation results, a personalised learning resource online recommendation method based on multidimensional feature extraction is proposed. Firstly, based on the feature expression and density parameters of user behaviour data, cluster the users. Secondly, extract users' time features, preference features, and learning resource features, and use feature matrices for efficient feature mining. Finally, the extracted personalised learning resource features are input into the self-organising maps (SOM) network, and through the resource scoring mechanism and similarity calculation process, recommendation prediction values are generated and sorted to form a personalised recommendation set. The experimental results show that this method can accurately provide resource solutions that meet user needs when the number of resources and users increase, and the recommendation coverage rate always remains above 90%. Journal: Int. J. of Networking and Virtual Organisations Pages: 86-101 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: personalised learning resources; resource recommendation; user clustering; time characteristics; preferential features; feature extraction; SOM network; K-means algorithm. File-URL: http://www.inderscience.com/link.php?id=145371 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:86-101 Template-Type: ReDIF-Article 1.0 Author-Name: XiaoYan Shi Author-X-Name-First: XiaoYan Author-X-Name-Last: Shi Author-Name: Ao Jiang Author-X-Name-First: Ao Author-X-Name-Last: Jiang Title: An optimisation strategy for the organisational structure of human resource management based on social networks Abstract: In order to solve the problems of high employee turnover rate, low task completion rate, and long decision-making time in traditional human resource management organisational structure optimisation methods, an optimisation strategy for the organisational structure of human resource management based on social networks was studied. Establish a human resources management organisational network, identify key individuals, teams, and potential problem areas within the organisation through intermediary centrality, weighted centrality, and clustering coefficients, identify existing problems in the human resources management organisational structure, and propose optimisation strategies for the human resources management organisational structure from multiple aspects such as optimising management structure, innovating management concepts, optimising talent allocation, and strengthening internal communication. The test results show that the employee turnover rate in the 10th month under the application of the proposed method is 8.36%, the task completion rate is 92.76%, and the minimum enterprise decision-making time is 4.5 min. Journal: Int. J. of Networking and Virtual Organisations Pages: 182-202 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: social networks; human resource management; organisational structure; optimisation strategies; intermediary centrality; weighted centrality; cluster coefficients. File-URL: http://www.inderscience.com/link.php?id=145372 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:182-202 Template-Type: ReDIF-Article 1.0 Author-Name: Xiao-Ying Fang Author-X-Name-First: Xiao-Ying Author-X-Name-Last: Fang Author-Name: Ming-Xing Lu Author-X-Name-First: Ming-Xing Author-X-Name-Last: Lu Title: High quality construction of innovation and entrepreneurship education system from the perspective of three comprehensive education Abstract: In order to overcome the problems of low quality index, innovative thinking path coefficient, and high error value in traditional methods, a high quality construction method of innovation and entrepreneurship education system from the perspective of three comprehensive education is proposed. Firstly, analyse the participants and influencing factors in the construction of the innovation and entrepreneurship education system from the perspective of comprehensive education. Secondly, establish a preliminary innovation and entrepreneurship education system. Finally, after evaluating the quality of the innovation and entrepreneurship education system, we will optimise and adjust the preliminary construction system to achieve high-quality construction of the innovation and entrepreneurship education system. The experimental results show that the quality index of the innovation and entrepreneurship education system constructed in this article is high, the path coefficient of innovative thinking is high, and the average evaluation error value is low. Journal: Int. J. of Networking and Virtual Organisations Pages: 158-181 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: three comprehensive education; innovation and entrepreneurship; education system; high quality; evaluating. File-URL: http://www.inderscience.com/link.php?id=145373 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:158-181 Template-Type: ReDIF-Article 1.0 Author-Name: Yang Zhang Author-X-Name-First: Yang Author-X-Name-Last: Zhang Author-Name: Jing Liu Author-X-Name-First: Jing Author-X-Name-Last: Liu Author-Name: Yunmin Xie Author-X-Name-First: Yunmin Author-X-Name-Last: Xie Title: The construction of innovation and entrepreneurship education ecosystem in universities based on social network analysis Abstract: In order to solve the problems of resource utilisation rate, achievement conversion rate, and low student satisfaction in traditional methods, a construction method of innovation and entrepreneurship education ecosystem in universities based on social network analysis is proposed. Analyse the concept of the innovation and entrepreneurship education ecosystem in universities, determine the relationship between the constituent elements, and use social network analysis methods to identify the bottlenecks and shortcomings of the innovation and entrepreneurship education ecosystem in universities. Starting from establishing innovative educational models, strengthening interdisciplinary integration, establishing innovation and entrepreneurship practice platforms, and strengthening industry and enterprise cooperation, will complete the construction of the innovation and entrepreneurship education ecosystem in universities. The test results of the example application show that the average resource utilisation rate of the proposed method is 83.27%, the average achievement conversion rate is 86.55%, and student satisfaction varies between 91.2 and 93.6%. Journal: Int. J. of Networking and Virtual Organisations Pages: 135-157 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: social network analysis; universities; innovation and entrepreneurship education; ecosystem; constituent elements; educational models. File-URL: http://www.inderscience.com/link.php?id=145374 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:135-157 Template-Type: ReDIF-Article 1.0 Author-Name: Anan Zheng Author-X-Name-First: Anan Author-X-Name-Last: Zheng Title: Research on financial systemic risk in the digital era and its dual pillar regulatory framework Abstract: To address the issues of elevated inaccuracy levels, prolonged verification durations, and diminished efficacy in risk management associated with conventional approaches, a financial systemic risk in the digital era and its dual pillar regulatory framework construction method are proposed. Analyse the impact of systemic financial risks on financial stability, combined with financial system risk measurement indicators such as CoVaR and Sharply value are used to identify financial system risks in the digital era. Based on the identification results of financial systemic risks in the digital era, a dual pillar regulation framework is constructed to achieve financial systemic risk regulation in the digital era from the perspectives of monetary policy and macro prudential policy. After experimental testing, it was found that the average risk misreporting rate of this method is 3.02%, the recognition time range is 0.21~0.63 s, and the average success rate of risk control is 96.17%. Journal: Int. J. of Networking and Virtual Organisations Pages: 102-118 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: digital era; financial systemic risk; dual pillar regulatory framework; risk measurement indicators; identify financial system risks; monetary policy; macro prudential policy. File-URL: http://www.inderscience.com/link.php?id=145375 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:102-118 Template-Type: ReDIF-Article 1.0 Author-Name: Yang Jin Author-X-Name-First: Yang Author-X-Name-Last: Jin Title: Study on digital financial fraud risk identification based on heterogeneous graph convolutional attention network Abstract: To enhance the accuracy of digital financial fraud risk identification and reduce the identification time, this paper introduces a digital financial fraud risk identification method utilising a heterogeneous graph convolutional attention network. Initially, financial business data is gathered and processed for data imbalance using generative adversarial networks. Subsequently, extreme learning machines are employed to extract spatially correlated features among various transactions. Following this, a robust graph convolutional attention network is constructed, a risk identification function is designed, and ultimately, the fraud data is fed into the graph convolutional neural network for training. The output data is categorised by transaction type to ascertain the presence of digital financial fraud risk. The results indicate that our method achieves a recognition accuracy exceeding 96%, with time consumption not surpassing 8.5 s, demonstrating that our method exhibits excellent recognition performance. Journal: Int. J. of Networking and Virtual Organisations Pages: 203-218 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: heterogeneous graph convolutional attention network; LSTM training; digital finance; fraud risk; extreme learning machine. File-URL: http://www.inderscience.com/link.php?id=145376 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:203-218 Template-Type: ReDIF-Article 1.0 Author-Name: Yingjun Liu Author-X-Name-First: Yingjun Author-X-Name-Last: Liu Author-Name: Kuineng Chen Author-X-Name-First: Kuineng Author-X-Name-Last: Chen Title: Dynamic mining of multimedia marketing information for products under the background of data driven Abstract: In order to solve the problems of low mining coverage and low product conversion rate in traditional marketing information dynamic mining methods, a new dynamic mining method of multimedia marketing information for products under the background of data driven is proposed. Using web crawler technology to crawl multimedia marketing information data of products, and extracting data features through sliding clustering. By using fuzzy clustering algorithm to perform fuzzy clustering on data features, a clustering dataset item set is constructed and merged into an item set to assign weights. Combined with association rules, dynamic mining of multimedia marketing information for products is achieved. Experimental results have shown that the mining coverage rate of this method is 91~97%, and the product conversion rate is 19.1% when the data volume is 8000. The mining coverage rate and product conversion rate are both at a high level, and the mining effect is good. Journal: Int. J. of Networking and Virtual Organisations Pages: 119-134 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: data driven; multimedia marketing information; dynamic mining; fuzzy clustering; association rules. File-URL: http://www.inderscience.com/link.php?id=145377 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:119-134 Template-Type: ReDIF-Article 1.0 Author-Name: Xin Liu Author-X-Name-First: Xin Author-X-Name-Last: Liu Author-Name: Lei Wang Author-X-Name-First: Lei Author-X-Name-Last: Wang Title: Construction of teaching service quality evaluation index system under the digital background Abstract: In order to solve the problems of low system integrity, poor closeness and reliability of evaluation indicators in traditional methods, a construction method of teaching service quality evaluation index system under the digital background is proposed. Complete the selection of evaluation indicator data through the ripple effect model. By calculating the Min's distance to measure the similarity of evaluation index data and removing data with high similarity, principal component analysis (PCA) is used to normalise and reduce the dimensionality of the data. Using extreme learning machine algorithm to classify and process evaluation indicators, and achieving research on the construction of teaching service quality evaluation indicator system. The case analysis results show that when the number of indicators is 1000, the completeness of the indicator system of the proposed method is 98%, the closeness is closer to 1, and the maximum reliability is 97%, which has the characteristics of high feasibility. Journal: Int. J. of Networking and Virtual Organisations Pages: 219-237 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: digital; teaching service quality; evaluation indicators; Min's distance; PCA; information gain. File-URL: http://www.inderscience.com/link.php?id=145390 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:219-237 Template-Type: ReDIF-Article 1.0 Author-Name: Jing Liao Author-X-Name-First: Jing Author-X-Name-Last: Liao Title: Evolution and coordination optimisation of regional innovation and entrepreneurship space layout under the background of social networks Abstract: To address the problems of poor adaptability of layout evolution parameters, poor convergence of constraint conditions, and high deviation in coordination optimisation in traditional methods, an evolution and coordination optimisation method of regional innovation and entrepreneurship space layout under the background of social networks has been designed. Determine the impact mechanism and layout constraints of the evolution of regional innovation and entrepreneurship spatial layout, and combine social networks to complete the analysis of the evolution of regional innovation and entrepreneurship spatial layout. Construct a spatial topology diagram for coordinating and optimising the layout of regional innovation and entrepreneurship spaces, determine the fitness of regional spatial layout parameters, and combine the coordination optimisation model to achieve coordinated optimisation of new entrepreneurial space layout parameters. The experimental findings indicate that the proposed method has good adaptability of the layout evolution parameters, good convergence of constraint conditions, low deviation in coordinated optimisation. Journal: Int. J. of Networking and Virtual Organisations Pages: 313-331 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: social networks; innovation and entrepreneurship space; layout evolution; layout constraints; impact mechanism; spatial topology diagram. File-URL: http://www.inderscience.com/link.php?id=145393 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:313-331 Template-Type: ReDIF-Article 1.0 Author-Name: Jinling Du Author-X-Name-First: Jinling Author-X-Name-Last: Du Title: Innovation of cross border e-commerce supply chain management mechanism under digital background Abstract: To address the challenges associated with sluggish inventory circulation, elevated product return percentages, and extended supply chain reaction durations within conventional approaches, an innovation method of cross border e-commerce supply chain management mechanism under digital background is proposed. After analysing the structure of cross-border e-commerce supply chain, based on the reliability and collaboration of the supply chain system, innovative strategies for cross-border e-commerce supply chain management mechanism under the digital background were analysed, including data-driven decision optimisation, digital upgrading of supplier management, intelligent inventory management, digital and intelligent logistics management, technological innovation and digital application, as well as risk management and emergency response. The findings from the trials indicate that the turnover ratio for inventory using the new technique fluctuates between 20.6% and 30.1%. Meanwhile, the typical rate of returns stands at 1.57%, and the supply chain's average reaction period is 12.64 days. The practical implementation has yielded positive outcomes. Journal: Int. J. of Networking and Virtual Organisations Pages: 291-312 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: digital background; cross border e-commerce; supply chain management; mechanism; innovation; reliability; collaboration. File-URL: http://www.inderscience.com/link.php?id=145394 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:291-312 Template-Type: ReDIF-Article 1.0 Author-Name: Ping Guo Author-X-Name-First: Ping Author-X-Name-Last: Guo Title: Multi-level logistics supply chain transportation scheduling method based on improved fruit fly algorithm Abstract: This paper proposes a logistics multi-level supply chain transportation scheduling method based on an improved fruit fly algorithm to address the problems of high transportation costs and low transportation efficiency in logistics multi-level supply chain transportation scheduling methods. Firstly, clarify the research scope and objectives by setting objective functions and constraints. Secondly, information exchange, mutation strategy, and probabilistic flight strategy were introduced to improve the fruit fly algorithm. Finally, based on the set algorithm parameters, use the improved Drosophila algorithm to evaluate the fitness of various logistics transportation plans and output the optimal results. After experimental verification, the total transportation time of the logistics transportation plan designed in this paper is 854 min, with 8 dispatched vehicles and a corresponding fuel cost of 2140.31 yuan. This method can effectively reduce transportation costs, improve logistics transportation efficiency, and has certain practical application value. Journal: Int. J. of Networking and Virtual Organisations Pages: 238-253 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: drosophila algorithm; multi-level logistics supply chain; information exchange and mutation strategies; probabilistic flight strategy; transportation scheduling. File-URL: http://www.inderscience.com/link.php?id=145395 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:238-253 Template-Type: ReDIF-Article 1.0 Author-Name: Yifan Wang Author-X-Name-First: Yifan Author-X-Name-Last: Wang Title: Network public opinion hotspot topic mining method based on improved support vector machine Abstract: The research on mining hotspot topic in online public opinion is of great significance for improving social management efficiency and promoting economic development. In order to overcome the problems of low accuracy, low recall, and long response time in traditional methods, a network public opinion hotspot topic mining method based on improved support vector machine (SVM) is proposed. Utilise distributed web crawlers to collect network public opinion data, and extract features of the collected network public opinion data through adaptive domain relationships. Introduce the least squares method to improve the SVM, input the feature extraction results into the improved SVM, and obtain the mining results of network public opinion hotspot topic. The experimental results show that the accuracy of network public opinion hotspot topic mining using this method varies between 96.3% and 98.3%, with an average recall rate of 97.7% and a response time of 5.9 s. Journal: Int. J. of Networking and Virtual Organisations Pages: 273-290 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: improve support vector machine; online public opinion; hotspot topic mining; distributed web crawlers; adaptive domain relationships; least squares method. File-URL: http://www.inderscience.com/link.php?id=145396 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:273-290 Template-Type: ReDIF-Article 1.0 Author-Name: Suying Nian Author-X-Name-First: Suying Author-X-Name-Last: Nian Title: Optimisation of internal control strategies in enterprises under the background of digital empowerment Abstract: In order to solve the problems of low internal risk identification rate, low accuracy of internal control strategy execution, and long response time in traditional methods, an optimisation method of internal control strategies in enterprises under the background of digital empowerment is proposed. Analysing the impact of digital empowerment on internal control in enterprises, identifying the problems existing in internal control, and proposing an optimisation path for internal control strategies from the perspectives of clarifying and integrating strategic objectives and internal control processes, accurately identifying and monitoring key control points (KCPs) in real time, balancing cost-effectiveness and risks, tailoring and continuously optimising internal control systems, and comprehensively optimising other key measures for internal control. The test results show that the maximum internal risk identification rate of this method is 97.8%, the maximum accuracy of internal control strategy execution is 97.7%, and the average response time is 37.09 min. Journal: Int. J. of Networking and Virtual Organisations Pages: 254-272 Issue: 1/2/3/4 Volume: 32 Year: 2025 Keywords: background of digital empowerment; internal control strategies in enterprises; optimisation of internal control; problems; balancing cost-effectiveness and risks; key measures. File-URL: http://www.inderscience.com/link.php?id=145399 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:32:y:2025:i:1/2/3/4:p:254-272 Template-Type: ReDIF-Article 1.0 Author-Name: Vaishali Satish Jadhav Author-X-Name-First: Vaishali Satish Author-X-Name-Last: Jadhav Author-Name: Pallavi Vasant Sapkale Author-X-Name-First: Pallavi Vasant Author-X-Name-Last: Sapkale Author-Name: Moresh M. Mukhedkar Author-X-Name-First: Moresh M. Author-X-Name-Last: Mukhedkar Title: Efficient call admission control in LTE networks with cascade feed forward network Abstract: This research proposes a cascade feed forward network (Cascade FFN) for the optimal call admission control (CAC) over networks. Initially, the long-term evolution (LTE) network is simulated and the incoming call is recognised as a new call or else handoff call. Likewise, the handoff call is identified by various channel parameters. Finally, the CAC is performed using the Cascade FFN, which is obtained by incorporating the deep feed forward network (DFN) and cascaded deep neuro-fuzzy network (DNFN). After the admission of the new user, number of active users in the individual cell is updated. The simulation is performed based on various parameters and the proposed model has gained throughput of 444058 bps, cell power of 54.267 dBm, delay of 0.081 s, user call drop of 940, call blocking probabilities of handoff and new user as 0.693, and 0.677; and the call dropping probabilities of handoff and new user is 0.733, and 0.740. Journal: Int. J. of Networking and Virtual Organisations Pages: 14-38 Issue: 1 Volume: 33 Year: 2025 Keywords: long term evolution (LTE) networks; CAC; call admission control; QoS; quality-of-service; DL; deep learning; FFN; feed forward network. File-URL: http://www.inderscience.com/link.php?id=149573 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:33:y:2025:i:1:p:14-38 Template-Type: ReDIF-Article 1.0 Author-Name: Kiran Kakade Author-X-Name-First: Kiran Author-X-Name-Last: Kakade Author-Name: Raj Kumar Rajak Author-X-Name-First: Raj Kumar Author-X-Name-Last: Rajak Author-Name: Ameya Patil Author-X-Name-First: Ameya Author-X-Name-Last: Patil Author-Name: Pooja Thorat Author-X-Name-First: Pooja Author-X-Name-Last: Thorat Author-Name: Jayant Brahmane Author-X-Name-First: Jayant Author-X-Name-Last: Brahmane Author-Name: Shilpa C. Shinde Author-X-Name-First: Shilpa C. Author-X-Name-Last: Shinde Title: Networks between industry academia: a statistical approach based on India Abstract: The National Agricultural Higher Education Project (NAHEP) was made by the Indian Council of Agricultural Research (ICAR) and the World Bank to improve higher education in agriculture in India. In the long run, this will allow farmers to have a better schooling system. The current study was done at national meetings with people from seven State Agricultural Universities (SAUs) across India, as well as people from business and academia. The goal was to improve 'collaboration between academia and industry' by bringing these groups together better. Based on the comments of 199 people from both school and business, the study shows that colleges and businesses need to join right away (p < 0.001). People think that these links will help higher education get better over time. Academic institutions think that these kinds of connections help students by making them more employable, giving them business skills, and giving them cash help. Journal: Int. J. of Networking and Virtual Organisations Pages: 87-99 Issue: 1 Volume: 33 Year: 2025 Keywords: academia; industry; collaboration; sustainable agricultural education; linkage; policy. File-URL: http://www.inderscience.com/link.php?id=149615 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:33:y:2025:i:1:p:87-99 Template-Type: ReDIF-Article 1.0 Author-Name: Son-Tung Le Author-X-Name-First: Son-Tung Author-X-Name-Last: Le Title: From personality to connection: the mediating role of tie strength in HEXACO traits and job networking behaviour Abstract: The HEXACO model and social network theory have been used to investigate the effect of personalities on level of the networking behaviour for finding employment, however, the mechanism explaining the relationships is unknown. The purpose of this research aims to examine the mediating role of tie strength in the relationships between HEXACO personalities and job search networking behaviour. The study applied the quantitative method with the sample of 773 university graduates collected at two points with a 3monthlagged time. Our findings indicate that Honesty-humility, Extraversion, Agreeableness, and Conscientiousness influence positively individuals' tie strength. Our study provides evidence that an individual tends to spend more time networking for stronger ties. The findings also demonstrate that tie strength plays a mediating role in the relationships between Honesty-humility, Extraversion, Conscientiousness, and job search networking behaviour. Implications for mentors, counsellors, and researchers are discussed. Journal: Int. J. of Networking and Virtual Organisations Pages: 39-66 Issue: 1 Volume: 33 Year: 2025 Keywords: HEXACO traits; tie strength; networking behaviour; job search; individual difference theory; social network theory. File-URL: http://www.inderscience.com/link.php?id=149616 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:33:y:2025:i:1:p:39-66 Template-Type: ReDIF-Article 1.0 Author-Name: Kiran Kakade Author-X-Name-First: Kiran Author-X-Name-Last: Kakade Author-Name: Chandrakant Varma Author-X-Name-First: Chandrakant Author-X-Name-Last: Varma Author-Name: Urmila Sandesh Sonavane Author-X-Name-First: Urmila Sandesh Author-X-Name-Last: Sonavane Author-Name: Jaya Chitranshi Author-X-Name-First: Jaya Author-X-Name-Last: Chitranshi Author-Name: Jayant Shaligram Brahmane Author-X-Name-First: Jayant Shaligram Author-X-Name-Last: Brahmane Author-Name: Shilpa C. Shinde Author-X-Name-First: Shilpa C. Author-X-Name-Last: Shinde Title: Social media for climate action in developing countries Abstract: In the Metaverse technology, also known as MVTECH, individuals connect with one another via the use of avatars. This technology creates an immersive virtual environment. With the MVTECH, a lot of opportunities were promised to be made available to a variety of industries, including higher education. A research model was developed by combining the essential elements of the 'unified theory of acceptance and use of technology' (UTAUT) with the variables of 'perceived curiosity' (PC) and 'extraversion' (EXT). 'Effort expectancy' (EE), 'performance expectancy' (PE), 'social influence' (SI), and 'facilitating conditions' (FC) are a few of these components. The information came from an online poll that was sent to 422 kids in Jordan schools. The 'structural equation modelling' (SEM) study showed that students' feelings about the Metaverse were greatly affected by their involvement in PE, FC, and EXT. The PC construct had a big effect on the EE construct. Journal: Int. J. of Networking and Virtual Organisations Pages: 1-13 Issue: 1 Volume: 33 Year: 2025 Keywords: metaverse; social sustainability; UTAUT; extraversion; curiosity; developing nations; environmental awareness; developing countries. File-URL: http://www.inderscience.com/link.php?id=149620 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:33:y:2025:i:1:p:1-13 Template-Type: ReDIF-Article 1.0 Author-Name: Hongli Liu Author-X-Name-First: Hongli Author-X-Name-Last: Liu Author-Name: Shuang Yang Author-X-Name-First: Shuang Author-X-Name-Last: Yang Title: Application of particle swarm optimisation in collaborative scheduling of logistics and supply chain Abstract: Traditional logistics and supply chain scheduling often focus on single-objective optimisation and ignore the complexity of multiple objectives, resulting in inefficiency and difficulty in cost control. This paper applies the particle swarm optimisation algorithm (PSO) to the collaborative scheduling of logistics and supply chain to improve transportation efficiency. This paper uses PSO to model logistics and supply chain scheduling problems, studies vehicle routing problems, and comprehensively considers multiple objectives such as transportation cost, inventory cost, and delivery time to optimise logistics transportation routes. Experiments show that after vehicle No. 1 was planned using the PSO algorithm, the transportation time was reduced by 2.1 h, the utilisation rate was as high as 98.2%. This shows that the PSO algorithm has significant advantages in logistics and supply chain collaborative scheduling, can effectively perform multi-objective optimisation, and has fast convergence speed and good stability. Journal: Int. J. of Networking and Virtual Organisations Pages: 67-86 Issue: 1 Volume: 33 Year: 2025 Keywords: logistics and supply chain management; PSO; particle swarm optimisation; collaborative scheduling; production and transportation; vehicle routing problem. File-URL: http://www.inderscience.com/link.php?id=149629 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijnvor:v:33:y:2025:i:1:p:67-86